Amazon Web Services provides a wide range of cloud-based services, including computation, storage, databases, analytics, networking, mobile, developer tools, management tools, Internet of Things (IoT), security, and enterprise applications. AWS SQS (Amazon Simple Queue Service) is a fully managed message queuing service for decoupling and scaling microservices, distributed systems, and serverless applications. Whereas, AWS Lambda is a computing service that allows you to run code without the need for server provisioning or management. Lambda executes your code on a high-availability compute infrastructure and manages the compute resources for you.

In this article, you will gain information about SQS Lambda Connection. You will also gain a holistic understanding of AWS SQS, its key features, AWS Lambda, its key features, steps to set up SQS Lambda Connection, and the benefits and limitations of SQS Lambda Connection. Read along to find out in-depth information about SQS Lambda Connection.

What is AWS SQS?

AWS SQS: SQS SendMessage logo| Hevo Data

Amazon SQS is a durable, secure, scalable, and available hosted Q that lets users integrate Software Systems and Components. It’s a hosted solution provided by Amazon, so you don’t need to manage the Service Infrastructure. SQS stores messages in transit between Applications and Microservices. Amazon provides a host of web service APIs, which users can access with a programming language supported by AWS SDK.

SQS eliminates the overhead and complexity associated with managing and operating message-oriented systems. Amazon SQS has no upfront cost or minimum fee, and every user gets the first million monthly requests free under the Amazon SQS Free Tier. However, users have to pay based on the content and number of requests and their interactions with Amazon S3 and the AWS Key Management Service. 

SQS offers an API for developers to connect with the service. SQS does not work as a database, so the user can’t decide which message to receive. However, they can choose how many messages they want to receive.

The main actions in high-level are:

  • Send Message: Send a request to a queue available for use by another service.
  • Receive Message: Another service can request to receive pending messages in the queue.
  • Delete Message: The user can remove the message from the queue upon proper processing.

Key Features of AWS SQS

Some of the key features of AWS SQS are as follows:

1) Queue Types

There are two types of queues: The standard queue and the FIFO queue. The standard queue option comes with unlimited throughput, at-least-once delivery, and best-effort ordering. FIFO queue offers high throughput, exactly-once processing, and first-in-first-out delivery features. The standard queue is useful for sending data between applications when throughput is important.

In contrast, users should use the FIFO queue when the order of events is important. The standard queue can support a nearly unlimited number of API calls per second, whereas the FIFO queue can only support up to 3,000 messages per second per API method. In the Standard queue, messages are occasionally delivered in a different order from which they were sent. Whereas the FIFO queue strictly preserves the order in which messages are sent and received.

2) Functionality

Amazon SQS offers functionalities such as batches of up to 10 messages or 256 KB; Payload size of up to 256 KB of text in any format; Unlimited queues and messages; Message retainment for up to 14 days in the queue; Queue sharing; and the ability to send and read messages simultaneously. It also offers long polling to reduce costs while receiving new messages. AWS SQS also offers Server-Side Encryption (SSE) to protect message content and Dead Letter Queues (DLQ) from handling messages that aren’t successfully processed. 

3) SQS with AWS infrastructure

You can pair the Amazon SQS messaging service with other AWS services such as Amazon DynamoDB, Amazon Redshift, Amazon Elastic Container Service (ECS), AWS Lambda, and Amazon Relational Database Service (RDS), Amazon Elastic Compute Cloud (EC2), and Amazon S3. It helps to make distributed applications more Reliable and Scalable. 

What is AWS Lambda?

SQS lambda: AWS Lambda Logo| Hevo Data
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AWS Lambda is the compute service offered by Amazon Web Services that allows you to without managing any server. It is an event-driven and serverless computing platform that runs code in response to events. AWS Lambda officially supports Python, Node.js Java, Go, Ruby, and C# language.

AWS Lambda uses a serverless computing service that executes Lambda functions to perform any computing task from serving web pages and processing data streams.

Key Features of AWS Lambda

Some of the main features of AWS Lambda are as follows:

1) Fault Tolerance

AWS Lambda helps users protect their code against individual machine or data center facility failures by maintaining compute capacity across multiple Availability Zones.

2) Auto Scaling

AWS Lambda can automatically scale for supporting the rate of incoming requests and invoking the code only when needed.

3) Flexible Resource Model

Users can choose the amount of memory they want to allocate to functions and it will CPU power, network bandwidth, and disk input/output (I/O) proportionally.

4) Automated Administration

AWS Lambda is capable of managing all the infrastructure for you to run your code and help you focus more on building backend services.

How does SQS Lambda work Together?

SQS queues can be configured as Lambda event sources. When messages arrive in an SQS queue, Lambda functions are automatically fired once you’ve set this up. Lambda may then scale up and down automatically based on the number of in-flight messages in a queue.

Lambda takes over and automates activities such as polling, reading, and removing messages from a queue. Successfully processed messages are discarded, while unsuccessful messages are routed to the DLQ or returned to the queue. These stages do not need to be configured directly inside a Lambda function.

Steps to Set up SQS Lambda Connection

The steps to set up SQS Lambda connection are as follows:

Step 1: Create SQS Queue

The steps to create SQS Queue while setting up SQS Lambda Connection are as follows:

  • Navigate to Simple Queue Service in the AWS Console.
  • Create a new SQS queue and call it whatever you want, like “TestSQSLambda.”
  • Click the “Quick-Create Queue” option after selecting the type Standard Queue.

Step 2: Create IAM Role

The steps to create IAM Role while setting up SQS Lambda Connection are as follows:

  • Go to Amazon Identity and Access Management (IAM).
  • Add the following policy to your Lambda execution role. Now, you can name it SQSLambda.
SQS Lambda: Lambda Execution Role| Hevo Data
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Step 3: Create a basic Lambda Function

The steps to create a basic Lambda Function while setting up SQS Lambda Connection are as follows:

  • Navigate to AWS Lambda in the AWS Console.
  • Create a new MySQSTriggerTest function.
  • In a similar fashion to the one shown below, edit the function and add basic function code.
SQS Lambda: Function Editing| Hevo Data
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  • Under the “Execution Role” section, select the role which we have defined earlier i.e., SQSLambda.

Step 4: Select SQS as a Trigger

The steps to select SQS as a Trigger while setting up SQS Lambda Connection are as follows:

  • Scroll through the list of triggers on the left under function configuration in the Designer and add the new SQS queue we built i.e, TestSQSLambda.
  • Select the “Add” button.
  • Now, click the “Save” button.
SQS Lambda: Select SQS as a Trigger| Hevo Data
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Step 5: Test your Trigger by creating a Test Event

The steps to test your trigger by creating a Test Event while setting up SQS Lambda Connection are as follows:

  • Select Configure test event from the upper right corner of the screen.
  • Select SQS from the Event template drop-down menu.
  • Keep the event’s default template.
  • Select the “Create” option. Then click the “Test” button

You should see the message Execution result: succeeded. If that’s the case, congratulations: your Lambda function just captured and processed a test SQS event!

Benefits of Setting up SQS Lambda Connection

Some of the benefits of setting up SQS Lambda Connection are as follows:

  • Fewer Moving Parts: Instead of using numerous services to achieve the same behaviour, such as Kinesis with SQS or SNS with SQS augmented by custom code, you can use a single SQS queue.
  • Reduced Costs: By consolidating numerous services into one, you can save money on cloud costs as well as time spent developing, debugging, and maintaining them.
  • Improved Fault Tolerance: Retries were difficult to obtain in previous systems. SQS has a built-in retry feature, as well as the option to use Dead Letter Queues (DLQ) for increased resilience.
  • Improved User Experience: SQS with Lambda’s simplicity and improved resilience means fewer production problems, faster debugging, and faster recovery when mistakes occur.

Limitations of Setting up SQS Lambda Connection

Some of the limitations of setting up SQS Lambda Connection are as follows:

  • Visibility Timeouts: messages are erased once a Lambda function has completed its execution. To ensure that all linked tasks may be completed, you must set the visibility timeout for queues and messages. Messages may reappear in the queue and trigger another Lambda invocation before being processed if this is not done.
  • SQS triggers are expensive: Lambda polls SQS queues for a long time before triggering the Lambda function when messages occur. SQS API calls made by Lambda are charged at the standard rate. Lambda may also need to add more pollers as needed, which will add to the cost.


In this article, you have learned about SQS Lambda Connection. This article also provided information on AWS SQS, its key features, AWS Lambda, its key features, steps to set up SQS Lambda Connection, and the benefits and limitations of SQS Lambda Connection.

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Share your experience of understanding setting up SQS Lambda Connection in the comment section below! We would love to hear your thoughts.

Manisha Jena
Research Analyst, Hevo Data

Manisha Jena is a data analyst with over three years of experience in the data industry and is well-versed with advanced data tools such as Snowflake, Looker Studio, and Google BigQuery. She is an alumna of NIT Rourkela and excels in extracting critical insights from complex databases and enhancing data visualization through comprehensive dashboards. Manisha has authored over a hundred articles on diverse topics related to data engineering, and loves breaking down complex topics to help data practitioners solve their doubts related to data engineering.

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